Regression & Logistic Models in Excel & Minitab
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Regression & Logistic Models in Excel & Minitab
This course is part of Predictive Analytics & Modeling with Minitab Specialization
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What you'll learn
Apply advanced regression and logistic modeling in Excel and Minitab.
Interpret outputs, diagnose model issues, and assess predictor significance.
Use ANOVA, t-tests, and correlation for business-focused data analysis.
Skills you'll gain
Tools you'll learn
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There are 4 modules in this course
By the end of this course, learners will be able to apply advanced regression techniques, interpret outputs, diagnose model issues, and implement logistic regression for real-world business applications. They will also master statistical tools in Excel and Minitab, enabling them to perform t-tests, ANOVA, correlation, and predictive modeling with confidence.
This course equips learners with both theoretical understanding and hands-on practice in predictive analytics. Through practical datasets, scatterplots, and business-focused case studies, learners will gain the ability to transform raw data into actionable insights. They will develop critical skills in identifying predictor significance, handling multicollinearity, and generating accurate regression equations. What makes this course unique is its balance of applied examples, rigorous diagnostics, and practical tool demonstrations. From consumer purchase analysis to business decision-making scenarios, learners will see how regression techniques directly support strategic outcomes. By completing this course, learners will be prepared to evaluate data-driven models, interpret complex statistical outputs, and apply regression analysis to solve real-world challenges.
This module introduces learners to advanced regression methods, focusing on predicted values, scatterplots, regression outputs, and diagnostics. Learners will gain practical skills in interpreting coefficients, testing significance, and identifying issues such as multicollinearity to ensure robust regression modeling.
What's included
11 videos3 assignments
11 videos•Total 93 minutes
- Generate Predicted Values•8 minutes
- Scatterplot Return RIL•7 minutes
- Basic Multiple Regression•9 minutes
- Basic Multiple Regression Continues•8 minutes
- Basic Multiple Regression - Interpretation•5 minutes
- Generate Basic Statistics•7 minutes
- Working on Scatterplot•4 minutes
- Dependent Variable Objective•12 minutes
- Concept of Multicollinearity•9 minutes
- Identify Dependent Variable Y•12 minutes
- Outputs and Observation•12 minutes
3 assignments•Total 50 minutes
- Predicted Values & Scatterplots•10 minutes
- Regression Outputs and Diagnostics•10 minutes
- Advanced Regression Techniques•30 minutes
This module emphasizes applied examples of regression, guiding learners through practical dataset analysis and interpretation. Learners will practice predicting values, visualizing results, and comparing models to develop strong data-driven decision-making skills.
What's included
11 videos3 assignments
11 videos•Total 89 minutes
- Interpretations - Example 3•10 minutes
- Calculate with and without Flux•7 minutes
- Scatterplot of Heart FLux Vs Insolation•6 minutes
- Interpretation of Datasets•12 minutes
- Implementation of Datasets•7 minutes
- Example 4 Observations•10 minutes
- Display Descriptive Statistics•7 minutes
- Predicted Values Example 4•10 minutes
- Scatterplot of Example 4•5 minutes
- Calculating IV - Multiple Regression•10 minutes
- Calculating Independent Multiple Regression•4 minutes
3 assignments•Total 50 minutes
- Applied Examples in Regression•10 minutes
- Predicted Values and Scatterplots•10 minutes
- Interpreting Regression Results•30 minutes
This module explores logistic regression foundations and real-world applications. Learners will understand categorical outcomes, interpret odds ratios, generate logistic models, and apply business-relevant case studies for actionable insights.
What's included
16 videos3 assignments
16 videos•Total 144 minutes
- Understanding Basic Logistic Scatter Plot•10 minutes
- Basic Logistic Scatter Plot Continues•8 minutes
- Generation of Regression Equation•11 minutes
- Tabulated Values•7 minutes
- Interpretation and Implementation on Dataset•11 minutes
- Interpretation and Implementation on Dataset Continues•8 minutes
- Output and Observation - Tabulated Values•9 minutes
- Business Metrics Example•7 minutes
- Example Two and Three Interpretations•7 minutes
- Regression Equation Group•8 minutes
- Interpretation and Implementation of Scatter Plot•9 minutes
- More on Implementation of Scatter Plot•6 minutes
- Plastic Case Strength•11 minutes
- Separate Equations•11 minutes
- Generation of Predicted Values•11 minutes
- Scatter Plot Strength Vs Temp•10 minutes
3 assignments•Total 50 minutes
- Logistic Regression Foundations•10 minutes
- Outputs and Case Studies•10 minutes
- Logistic Regression & Applications•30 minutes
This module focuses on applying regression and statistical tools to real-world business and consumer data. Learners will use Excel and Minitab for analysis, implement tests like t-test, ANOVA, and correlation, and generate actionable insights for business applications.
What's included
18 videos4 assignments
18 videos•Total 165 minutes
- Data of Cereal Purchase•11 minutes
- Children View Ad and RE•10 minutes
- Predicted Values for Individual Customers•12 minutes
- Income Independent Variable•9 minutes
- Example of Credit Card Issuing•11 minutes
- Example Five - Tabulated Values•9 minutes
- Generating Outputs•9 minutes
- Example Five Interpretations•11 minutes
- Situations Income•10 minutes
- Adding Predicted Values•7 minutes
- Scatter Plot Scale•9 minutes
- Using Data Analysis Toolpak•7 minutes
- Implementation of Descriptive Statistics•8 minutes
- Descriptive statistics - Input Range•7 minutes
- Implementation of ANOVA•6 minutes
- Implementation of T - Test•6 minutes
- Implementation Using Correlation•10 minutes
- Implementation Using Regression•12 minutes
4 assignments•Total 60 minutes
- Business and Consumer Data•10 minutes
- Example-Based Predictions•10 minutes
- Using Excel and Minitab for Analysis•10 minutes
- Business Applications & Data Analysis Tools•30 minutes
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